More about BacMet database


BacMet is maintained at the University of Gothenburg, Sweden. Please contact Chandan Pal or Joakim Larsson for more information.

We have divided this section into

  1. Update details
  2. Data source and inclusion criteria
  3. Database schema
  4. Database Structure and Creation workflow


Antibacterial biocides and metals have the potential to select for antibiotic resistant bacteria through co- and cross-resistance mechanisms. Understanding the importance of biocides and metals in this process requires information about the involved genes and their DNA and protein sequences. Therefore, to facilitate the research on co-selection, we have developed BacMet, a database of biocide and metal resistance genes with highly reliable content. In BacMet version 1.0, there were 470 resistance genes in the experimentally confirmed database whereas the predicted database had 25,477 resistance genes. Currently, in BacMet version 1.1, the experimentally confirmed database contains 704 resistance genes, whereas the predicted database contains 40,556 resistance genes.

1. Update details

This version of BacMet database was last updated on January 18, 2014. The database is updated regularly through formalized literature searches, invitations to leading experts and through reviewed user-suggestions.

2. Data source and inclusion criteria

An extensive review of the scientific literatures related to biocide- and metal-resistance is the foundation of BacMet. A gene has been considered experimentally confirmed only if the removal/mutation or insertion/overexpression of the gene resulted in a decreased or increased phenotypic resistance, respectively. Genes that are part of an experimentally confirmed resistance operon have been included. Metadata, such as source organism, plasmid/chromosomal location and gene description, were collected from publicly available resources, including NCBI GenBank, UniprotKB, and the Transporter Classification Database (TCDB). All data and metadata have been manually scrutinized before included into BacMet.

From 421 PubMed articles, a core dataset of 470 experimentally confirmed genes (as of 30 October 2013) was created (referred to as 'BacMet Experimentally Confirmed database'). This core-dataset was used as to obtain homologous sequences from NCBI non-redundant protein database using BLAST (version 2.2.25), forming the larger 'BacMet Predicted database'. A multistage filtering was performed to collect homologous sequences. Initially, a fixed e-value cutoff of ≤ 0.01 followed by a fixed coverage cutoff of 80% was used for all sequence matches. Additionally, a 90% fixed identity cutoff was applied for protein sequences originating from plasmids, while an individual identity cut-off was set for each chromosomal sequence. Redundancy was removed by clustering all homologous protein sequences with a 100% identity cut-off using USEARCH (version 5.2.32).

Only compounds or active substances that are used in biocidal products listed in the review programme as 'existing in the biocidal products in EU market' by European Commission Regulation (EC) No 1451/2007 and other compounds that are not listed in the EC list but have been used as biocides were classified as 'biocides'. Classical antibiotic compounds were excluded as they are covered in antibiotic resistance gene databases but genes confer resistance to both antibiotics and biocides have been included. The search for antibacterial biocide resistance genes also resulted in the identification of resistance genes to other chemical compounds that have experimental evidence as potentially toxic to bacteria, but generally not used as biocides, i.e. not used with the intention to kill bacteria, such as dyes, organic solvents etc. In principle, such compounds do also have the potential to co-select for antibiotic resistance and shown to be conferring resistance to, by genes that are resistant to other biocides and metals as well, we have therefore included these genes in the database, but under the heading 'other compounds'.

3. Database schema

Both BacMet databases ('BacMet Experimentally Confirmed database' and 'BacMet Predicted database') are built on Apache server 2.2.3. The database tables are stored in MySQL server 5.0.77 relational databases and operated in RedHat Linux systems. The web-interface was created using HTML, PHP and Cascading style sheets (CSS). CGI-Perl programming language was used for retrieving data from MySQL databases and present result output to the web-interface.

4. Database Structure and Creation workflow

BacMet creation



BacMet database/website is designed and maintained by Chandan Pal

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